Automatic selection of video from active cameras

ABSTRACT

A method according to one embodiment includes: receiving, by a processing system, sensor data from a sensor device carried by a user or attached to the user&#39;s sports equipment during a sporting activity; identifying, by the processing system and based on the sensor data, an event engaged in by the user during a time period; determining, based on the sensor data, a position of the user during the event; identifying a camera that is operational and has the user in view during at least a portion of the time period; and selecting video footage of the event from the identified camera.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/562,395, entitled “AUTOMATIC SELECTION OF VIDEO FROM ACTIVE CAMERAS,”filed Dec. 5, 2014, which is a continuation of U.S. patent applicationSer. No. 13/734,818 entitled “AUTOMATIC DIGITAL CURATION AND TAGGING OFACTION VIDEOS,” filed Jan. 4, 2013, now U.S. Pat. No. 8,929,709, whichclaims priority to U.S. Prov. Pat. App. Ser. No. 61/689,654, filed Jun.11, 2012 entitled “Auto Digital Curation And Tagging Of Action Videos,”the entire disclosures of which are hereby incorporated herein byreference.

This application includes material which is subject to copyrightprotection. The copyright owner has no objection to the facsimilereproduction by anyone of the patent disclosure, as it appears in thePatent and Trademark Office files or records, but otherwise reserves allcopyright rights whatsoever.

FIELD

The present invention relates in general to the field of devices forrecording video, and in particular to methods and apparatuses forautomatic digital curation and tagging of action videos.

BACKGROUND

The wide availability of portable cameras has led to an explosion ofshort self-made and professional videos. Many of these videos,especially made with POV (Point Of View) action cameras, are related toaction sports such as downhill skiing, snowboarding, surfing, mountainbiking, etc. The YouTube web site, for example, contains thousands ofsuch videos.

At the same time, the very number and popularity of these videos createdits own problem. Firstly, it has become very difficult to find a videoof interest when the event of interest is not explicitly associated withthe video by its creators. Secondly, since most of the videos are madeby amateurs and are not edited, users have to watch the entire videoeven if they are interested only in some particular portion of it e.g.when a snowboarder jumps or a skier has a particularly fast portion of arun, or any other particular events within a larger video.

At the same time the wide popularity of portable devices with GPS andother sensors allows accurate measurement, storage, and classificationof action sport activities. Therefore, if video and performance data canbe synchronized in time and space then video footage can be annotated,edited, selected, and tagged based on the performance matrix of aparticular activity that was filmed.

A person searching or viewing such video may desire to find particularvideo or portions of a video. For example, such person may want tosearch for video that shows snowboarding jumps with air time longer thanone second. However, this would be impractical or impossible using thecurrently available means for video tagging which typically use onlysemantic and text video descriptions.

Another issue associated with many action videos is that they are madeby one person and performance data for the video “subject” are collectedby the sensors collocated with the video subject who is a differentperson.

Attempts have been made to mark video during capture for quickselection. However, such solutions typically use tags that are based ontext that is created by others or found in the video.

U.S. Pat. No. 7,624,337 and U.S. Pat. No. 7,823,055 disclose a solutionthat uses text, including text in the video, to create tags and metadata for later use in video searching.

U.S. Pat. No. 5,832,171 to Heist, et al. describes synchronization ofvideo and text where the text was created for the video.

U.S. Pat. No. 4,873,585 to Blanton et al teaches a system that allowsselection of images of particular motions from a video to allow easyaccess to these images. However, this requires operator intervention anddecision making.

U.S. Pat. No. 7,483,049 to Aman et al. discloses creation of a databaseof videos of sport motions. However, the video has to be created in avery controlled environment by multiple cameras with athletes markedwith visible or invisible markers that can be identified in the video.

There is also a body of work on triggering video by particular events,mostly traffic violations. U.S. Pat. No. 7,986,339 to Higgins describesa system capable of recording and analyzing still and video images of atraffic violation. However, the video recording is triggered by anoutside physical signal that is generated by a vehicle, e.g. laser orDoppler radar. U.S. Pat. No. 6,919,823 to Lock and U.S. Pat. No.7,633,433 to Behrens are similar, with a triggering signal generated bya red light change or a laser beam interrupted after the red lightchange.

In addition, in the above cases, the relative position of a camera andthe video subject are known in advance, and so the solution does notprovide any time and space domain search to match the event and thevideo footage.

SUMMARY

In an embodiment, the present disclosure provides a method and a systemthat allows synchronization of the video and the correspondingperformance data, and then tagging and/or editing of the video based onthe performance data. The video and the performance data can becollected by a collocated device (i.e., the same device) or differentdevices and different users. The video and performance data could alsobe stored in the same device or be stored in different devices ordatabases. The invention can thus provide matching of video andperformance data from different data sets or different databases andthen automatic editing, annotation, and tagging of the video. This canbe done even if the video and performance data were recordedindependently and without explicit knowledge of other activity.

A method according to one embodiment includes: receiving, by aprocessing system, sensor data from a sensor device carried by a user orattached to the user's sports equipment during a sporting activity;identifying, by the processing system and based on the sensor data, anevent engaged in by the user during a time period; determining, based onthe sensor data, a position of the user during the event; identifying acamera that is operational and has the user in view during at least aportion of the time period; and selecting video footage of the eventfrom the identified camera.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of theinvention will be apparent from the following more particulardescription of preferred embodiments as illustrated in the accompanyingdrawings, in which reference characters refer to the same partsthroughout the various views. The drawings are not necessarily to scale,emphasis instead being placed upon illustrating principles of theinvention.

FIG. 1 shows a flowchart illustrating an embodiment of a method forautomatic selection of a desired portion of video footage from an actionvideo when sensors are collocated with the video camera.

FIG. 2 shows a three-dimensional diagrammatic view illustrating ascenario in which a skier's trajectory crosses a field of view of CameraA but does not cross a field of view for Camera B.

FIG. 3. shows a flowchart illustrating an embodiment of an appropriatealgorithm which searches a database of active cameras.

FIG. 4. shows a block diagram illustrating organization of the video andperformance databases in accordance with an embodiment of the invention.

FIG. 5 shows a flowchart illustrating a process for using performancemeta data for search simplification.

DETAILED DESCRIPTION

Reference will now be made in detail to the preferred embodiments of thepresent invention, examples of which are illustrated in the accompanyingdrawings.

The present invention is described below with reference to blockdiagrams and operational illustrations of a system and method forautomatic digital curation and tagging of action videos. It isunderstood that each block of the block diagrams or operationalillustrations, and combinations of blocks in the block diagrams oroperational illustrations, may be implemented by means of analog ordigital hardware and computer program instructions. These computerprogram instructions may be stored on computer-readable media andprovided to a processor of a general purpose computer, special purposecomputer, ASIC, or other programmable data processing apparatus, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, implement thefunctions/acts specified in the block diagrams or operational block orblocks. In some alternate implementations, the functions/acts noted inthe blocks may occur out of the order noted in the operationalillustrations. For example, two blocks shown in succession may in factbe executed substantially concurrently or the blocks may sometimes beexecuted in the reverse order, depending upon the functionality/actsinvolved.

In an embodiment, a user is equipped with a sensor-based device thatrecords his/her motions. The sensor-based device may be, e.g., aportable device that includes GPS and inertial sensors. Also provided isa processing system, which may be embedded in the sensor-based device,may be a separate device, or may be server-based, that is capable ofdetecting such events as jumps, flips, rotations, high speed, fastturns, etc. As a result, a detailed record of the motions with detailedtrajectory, speed, acceleration, jumps, tricks, etc. is created andstored in a performance database. Also provided is a video camera forwhich location, time, and, optionally, direction information are knownfor the time when video is taken. The camera may be collocated with thesensors, or may be an independent device.

The following is a non-limiting example of the operation of the systemand method in accordance with an embodiment of the invention. A videocamera records a sports activity that occurs between time t=T_(start)and t=T_(end). In this example, the same activity performance parametershave also been recorded using a set of sensors. A particular event ofinterest, e.g. a jump, is detected using sensory data at time t=t_(k),T_(start)<t_(k)<T_(end). Then, if sensory data and video aretime-synchronized, the video footage of the event of interest can be cutout between time t_(k−T) and t_(k+T) where T is a half period of thedesired video footage. In an embodiment, if video is shorter than adesired time 2T, then the entire video is used. Time synchronizationbetween video and sensor data can be conducted using GPS Time stamps, orwireless network time stamps, or any other method known to those who areproficient in the art

FIG. 1 shows a flowchart illustrating an embodiment of a method forautomatic selection of a desired portion of video footage from an actionvideo when sensors are collocated with the video camera. Time andposition coordination allows a system to automatically associate videofootage and sport performance. If camera position, direction, and focuslength are known, then a more sophisticated paring between video andsensory data can be made. The method begins with a step 101 wherein timeis synchronized between video and sensor records. At step 103, an eventof interest is selected based on sensor data. This event may be, e.g., ajump, a flip, a rotation, a high speed portion, a turn, a fast turn, orany other finite portion of a user's performance that may be ofinterest. At step 105, the processing device automatically determineswhere the event of interest occurs in the sensor data, with t=T_(sns).Various systems and methods for identifying an event of interest insensor data are taught, for example, in U.S. patent application Ser. No.13/612,470 entitled “Method and Apparatus for Determining SportsmanJumps Using Fuzzy Logic” filed Sep. 12, 2012, the entire disclosure ofwhich is incorporated herein by reference.

With continued reference to FIG. 1, at step 107, the time determined instep 105 above is transferred into the time frame of video in the videodatabase such that Tv=Sync(T_(sns)). Then, at step 109, the videobetween Tv−T: Tv+T is selected. Performance data is then embedded(displayed, annotated) in the video data at step 111. The video data maybe automatically tagged with performance data at step 113. The automatedtagging may include user name, event time and location, and the keyperformance characteristics such as speed, slope value, jump time and/orheight, flip angle, or trade name, etc. Alternatively, or in addition,the video may then be automatically edited step 111 is complete.

It will be understood by those skilled in the art that a similaroperation can be done by selecting an appropriate performance segmentwhen a video is short and a performance record covers a much longeroverlapping time period.

FIG. 2. shows a three-dimensional diagrammatic view illustrating ascenario in which a skier's trajectory crosses the field of view ofCamera A but does not cross the field of view for Camera B. If an eventof interest occurs during the time that camera A is operational then theappropriate footage can be identified and selected. The trajectory ofEvent B does not cross any camera field of view, and cannot besynchronized. This implementation illustrates a possible case wheremultiple unattended cameras constantly record any activity in theirfield of view and then a video of interest is auto selected based on theperformance, time, and location data that are collected separately.

FIG. 3. shows a flowchart illustrating an embodiment of an appropriatealgorithm which searches a database of active cameras. At step 301, anevent of interest is identified using sensor data. As noted above, suchevent may be, a jump, a flip, a rotation, a high speed portion, a turn,a fast turn, or any other finite portion of a user's performance thatmay be of interest. Once the event is identified, at step 303 theprocessing system determines the geographic position and time durationof the event. At step 305, the processing system finds all cameras thatare operational at time T_(k) (determined in step 303 above). If thereare no cameras operational, as determined at step 307, the process ends.Otherwise, the process proceeds to step 309, in which operationalcameras or camera data are time synchronized with sensors or sensordata. Once the operational cameras or their data are time synchronizedwith sensors or sensor data, the process proceeds to select, at step311, a subset of the cameras that has the position of the event (asdetermined above in step 303) in their field of view. If there are nosuch cameras, as determined at step 313, the process ends. Among thepreviously selected subset of cameras, a further subset of cameras isselected at step 315, this further subset being those cameras or cameradata that meet other criteria. Examples of such other criteria include,e.g., the camera that has the best focus. From the further subset ofcameras, the video footage recorded at time T_(k−T): T_(k+T) is selectedat step 317. At step 319, the performance data for the event ofinterest, or for all of the performance, is embedded into the videodata. Finally, the video data is tagged with performance data as well aswith other information—time, location, user, at step 321.

FIG. 4. shows a block diagram illustrating an example of theorganization of the video and performance databases in accordance withan embodiment of the invention. FIG. 5 shows a flowchart illustrating aprocess for using performance meta data for search simplification.

Thus, an embodiment of the presently disclosed system and method allowsediting, annotation, and searching of an individual video or a videolibrary by performance characteristics. A subject selection can befurther refined by selecting performance data from the users that belongto a particular subgroup, say “friends”. Suppose several users haveperformance data trajectory that corresponds to a particular video clip.However, only one user among them belongs to the “friends” subgroup ofthe person who made the video. Then the performance data of this“friend” can be automatically selected to be synchronized with thevideo. This resolves a common situation wherein a person records a videoof his or her friends and other people activity are also recorded in theframe. The automatic selection in accordance with various embodiments ofthe invention can further improve the performance of the system andsimplifies the process of video creation.

The processing steps described herein may be performed on one or morecomputing devices. For example, the steps may be performed on anycombination of (a) a portable data collection device carried by theuser, (b) a portable video recording computing device carried by aspectator at a sporting event or by a user participating in the event,or (c) a remote server computing device. An example of portable datacollection devices is a portable computing device or smartphone with anaccelerometer and GPS capability therein. Examples of a portable videorecording computing device include a video camera with processingcapability, or a smart phone with video recording hardware and software.Each such computing device may comprise, e.g., a processor for carryingout instructions; computer readable media such as static memory and/ordynamic memory for storing computer program instructions; input meanssuch as a touch screen, keyboard, voice input, mouse, or the like; anetwork interface for communicating over a wireless and/or wirednetwork, and a user interface such as a display, speaker, and hard orsoft buttons. The portable data collection device may further include anaccelerometer, such as a three-axis accelerometer, and may also includea GPS receiver and the capability to determine its position using thesame. The remote server computing device may be a device that is remotefrom the portable data collection device. For example, server or desktopcomputer may be provided and process raw or preprocessed accelerometerdata from the portable data collection device. The transmission of datafrom a portable data collection device to the computing device or to theremote server computing device may be performed via a wireless and/orwired network interface associated with the portable data collectiondevice and a wireless and/or wired network interface associated with theremote server or remote desktop computer.

The above embodiments and preferences are illustrative of the presentinvention. It is neither necessary, nor intended for this patent tooutline or define every possible combination or embodiment. The inventorhas disclosed sufficient information to permit one skilled in the art topractice at least one embodiment of the invention. The above descriptionand drawings are merely illustrative of the present invention and thatchanges in components, structure and procedure are possible withoutdeparting from the scope of the present invention as defined in thefollowing claims. For example, elements and/or steps described aboveand/or in the following claims in a particular order may be practiced ina different order without departing from the invention. Thus, while theinvention has been particularly shown and described with reference toembodiments thereof, it will be understood by those skilled in the artthat various changes in form and details may be made therein withoutdeparting from the spirit and scope of the invention.

What is claimed is:
 1. A computer-implemented method, comprising:receiving, by a processing system, sensor data from a sensor devicecoupled to a user during a sporting activity; identifying, by theprocessing system and based on the sensor data, an event engaged in bythe user during a time period; identifying a camera that is operationaland has the user in view during at least a portion of the time period;and selecting video footage of the event from the identified camera. 2.The method of claim 1, further comprising synchronizing video from theidentified camera with the received sensor data using a common source.3. The method of claim 1, wherein the common source comprises a wirelessnetwork time stamp.
 4. The method of claim 1, wherein selecting videofootage of the event further includes selecting at least one frame ofthe video footage and performing a digital zoom on the at least oneframe to select a portion of the frame based on a predeterminedcriteria.
 5. The method of claim 1, wherein identifying the cameraincludes: identifying a plurality of cameras that are operational duringthe time period; and identifying a subset of the operational camerasthat have the user in view during the time period; and selecting acamera from the subset of operational cameras based on at least onecriteria.
 6. The method of claim 5, wherein the at least one criteriaincludes a focus level of each camera in the subset.
 7. The method ofclaim 1, further comprising embedding performance data related to theevent in the selected video footage.
 8. The method of claim 1, furthercomprising tagging the selected video footage with one or more of:performance data related to the event, time information, locationinformation, and information regarding the user.
 9. The method of claim1, wherein the sensor data includes inertial data.
 10. The method ofclaim 1, wherein the sensor data includes at least one of: position dataand time data.
 11. The method of claim 1, wherein the identified eventis selected from the group consisting of: a jump, a flip, a rotation, ahigh speed portion, a turn, and a fast turn.
 12. The method of claim 1,wherein the processing system is embedded in the sensor device.
 13. Themethod of claim 1, wherein the processing system is a separate devicefrom the sensor device.
 14. The method of claim 1, wherein theprocessing system comprises a server.
 15. The method of claim 1, whereinthe sensor device is co-located with a camera that generates said videodata.
 16. The method according to claim 1, wherein the sensor device isseparate and independent from the camera that generates the videofootage.
 17. A system, comprising: a processor; and memory coupled tothe processor and storing instructions that, when executed by theprocessor, cause the system to: receive sensor data from a sensor devicecoupled to a user during a sporting activity; identify based on thesensor data, an event engaged in by the user during a time period;identify a camera that is operational and has the user in view during atleast a portion of the time period; and select video footage of theevent from the identified camera.
 18. A computer program productcomprising a non-transitory computer readable storage medium storinginstructions that, when executed by a computing device, cause thecomputing device to: receive sensor data from a sensor device coupled toa user during a sporting activity; identify based on the sensor data, anevent engaged in by the user during a time period; identify a camerathat is operational and has the user in view during at least a portionof the time period; and select video footage of the event from theidentified camera.